DataOps seeks to provide the tools, processes, and structures for significant increase in data.

Having an Agile approach to designing, implementing and maintaining a distributed data architecture DataOps aims to create business value from big data. DataOps applies to the entire data lifecycle from data preparation to reporting, and recognizes the interconnected nature of the data analytics team and information technology operations.


According to IDC, The volume of data is forecast to grow at a rate of 32% CAGR to 180 Zettabytes by the year 2025.

DataOps is a data management framework that borrows from the agile methodology, lean manufacturing and DevOps to democratize data, build trust and improve team collaboration. It is very critical to get a right DataOps team. We at crossML have extensive experience with right tools and processes required for this setup. Our team help customers bring speed and agility to end-to-end data pipelines process.

Data Pipeline Orchestration

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. We help businesses identify and setup right data pipeline tools. We expertise in tools like Apache Airflow, Apache Oozie, DataKitchen, Reflow etc

Data Sources
and ETL

We help businesses make right decisions for choosing data source and setting up ETL processes with Data lakes and Data warehouses. Poor implementation leads to no curation, including little to no active management throughout the data life cycle and little to no contextual metadata and Data Governance

DataSecOps and DataGovOps

Reduce the time to get quality results through reliable and efficient machine learning lifecycle management with any security concerns. We setup the right data governance tools and processes. Our expert teams ensure unified development, security, and seamless ML operations

BI, Data Analytics and Big Data

Eliminate Gaint data silos and setup modern data architecture with right big data tools on cloud or on-prem servers for better handling and managment of data. With the right infrastructure in place Data Analytics and BI teams can identify parterns and generate critical business insights.

Why you should use DataOps?

  • Manage and use increasing data volumes effectively while reducing the cycle time of data analytics.
  • DataOps moves code and configuration continuously from development environments into production, leading to near real-time data insights.
  • With reduced inefficiencies and improved quality, data science teams can focus on their area of expertise; creating new models and analytics that fuel business innovation and create a competitive advantage.
  • Catch incorrectly processed data before it is passed downstream.
Cloud Benefits

Why choose crossML As your Data Engineering partner?

  • Estimate upfront costs, timelines, and required licensing for DataOps journey.
  • Design a well-planned fast, secure, and seamless data pipeline that enable seamless data ingestion, processing and Visualization.
  • Optimised architecture for both on-premise and cloud implementation of vaious DataOps tools and services.
  • We manage 100% of your DataOps lifecycle to enable agility and responsiveness, with no compromise on data security & governance.
  • Certified and skilled skilled professionals that design, develop monitor and support your dataOps processes.
  • Expertise on various Data lakes, data warehouses, big data, CI/CD, Cloud technologies.

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